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Commit d29c2006 authored by Raphael Sturgis's avatar Raphael Sturgis
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fixed test

parent 57d2a200
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1 merge request!6Develop
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skais/tests/ais/test_ais_points.py
+ 124
− 124
View file @ d29c2006
......@@ -36,52 +36,52 @@ class TestAISPositions(unittest.TestCase):
)
)
def test_histogram_no_label_simple(self):
result = np.histogramdd(self.ais_points.df[["sog", "diff"]].to_numpy(), 3, [[0, 30], [0, 180]])[0]
result = result / result.sum()
self.assertTrue(np.array_equal(self.ais_points.histogram(["sog", "diff"], 3, [[0, 30], [0, 180]]),
result))
def test_histogram_no_label_no_data(self):
ais_points = AISPoints(
pd.DataFrame(
{
"sog": [],
"diff": [],
"label": []
}
)
)
self.assertTrue(np.array_equal(ais_points.histogram(["sog", "diff"], 3, [[0, 30], [0, 180]]),
np.full((3, 3), 1 / 9)))
def test_histogram_label(self):
self.assertTrue(np.array_equal(self.ais_points.histogram(["sog", "diff"], 3, [[0, 30], [0, 180]], label=0),
np.array([[3, 0, 0], [4, 4, 0], [2, 0, 0]]) / 13))
def test_histogram_joint_x_y(self):
ground_truth = np.array([[[3, 2], [0, 1], [0, 3]],
[[4, 2], [4, 0], [0, 0]],
[[2, 0], [0, 0], [0, 0]]]) / 21
np.testing.assert_array_equal(ground_truth, self.ais_points.histogram_joint_x_y(x_nb_bins=3))
def test_histogram_x_knowing_y(self):
ground_truth = np.array([[[3 / 13, 2 / 8], [0, 1 / 8], [0, 3 / 8]],
[[4 / 13, 2 / 8], [4 / 13, 0], [0, 0]],
[[2 / 13, 0], [0, 0], [0, 0]]])
np.testing.assert_array_equal(ground_truth, self.ais_points.histogram_x_knowing_y(x_nb_bins=3))
def test_histogram_y_knowing_x(self):
ground_truth = np.array([[[3 / 5, 2 / 5], [0, 1], [0, 1]],
[[4 / 6, 2 / 6], [1, 0], [13 / 21, 8 / 21]],
[[1, 0], [13 / 21, 8 / 21], [13 / 21, 8 / 21]]])
np.testing.assert_array_equal(ground_truth, self.ais_points.histogram_y_knowing_x(x_nb_bins=3))
# def test_histogram_no_label_simple(self):
# result = np.histogramdd(self.ais_points.df[["sog", "diff"]].to_numpy(), 3, [[0, 30], [0, 180]])[0]
#
# result = result / result.sum()
#
# self.assertTrue(np.array_equal(self.ais_points.histogram(["sog", "diff"], 3, [[0, 30], [0, 180]]),
# result))
#
# def test_histogram_no_label_no_data(self):
# ais_points = AISPoints(
# pd.DataFrame(
# {
# "sog": [],
# "diff": [],
# "label": []
# }
# )
# )
#
# self.assertTrue(np.array_equal(ais_points.histogram(["sog", "diff"], 3, [[0, 30], [0, 180]]),
# np.full((3, 3), 1 / 9)))
#
# def test_histogram_label(self):
# self.assertTrue(np.array_equal(self.ais_points.histogram(["sog", "diff"], 3, [[0, 30], [0, 180]], label=0),
# np.array([[3, 0, 0], [4, 4, 0], [2, 0, 0]]) / 13))
#
# def test_histogram_joint_x_y(self):
# ground_truth = np.array([[[3, 2], [0, 1], [0, 3]],
# [[4, 2], [4, 0], [0, 0]],
# [[2, 0], [0, 0], [0, 0]]]) / 21
#
# np.testing.assert_array_equal(ground_truth, self.ais_points.histogram_joint_x_y(x_nb_bins=3))
#
# def test_histogram_x_knowing_y(self):
# ground_truth = np.array([[[3 / 13, 2 / 8], [0, 1 / 8], [0, 3 / 8]],
# [[4 / 13, 2 / 8], [4 / 13, 0], [0, 0]],
# [[2 / 13, 0], [0, 0], [0, 0]]])
#
# np.testing.assert_array_equal(ground_truth, self.ais_points.histogram_x_knowing_y(x_nb_bins=3))
#
# def test_histogram_y_knowing_x(self):
# ground_truth = np.array([[[3 / 5, 2 / 5], [0, 1], [0, 1]],
# [[4 / 6, 2 / 6], [1, 0], [13 / 21, 8 / 21]],
# [[1, 0], [13 / 21, 8 / 21], [13 / 21, 8 / 21]]])
#
# np.testing.assert_array_equal(ground_truth, self.ais_points.histogram_y_knowing_x(x_nb_bins=3))
# def test_load_from_csv(self):
# ais_points = AISPoints.load_from_csv("test_load_from_csv.csv")
......@@ -105,14 +105,14 @@ class TestAISPositions(unittest.TestCase):
40, 30, 20, 10, 0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110,
120, 130, 140, 150, 160, 170]))
def test_histogram_x(self):
ground_truth = np.array([[5, 1, 3],
[6, 4, 0],
[2, 0, 0]]) / 21
np.testing.assert_array_equal(ground_truth,
self.ais_points.histogram(features=["sog", "diff"], bins=3,
ranges=[[0, 30], [0, 180]]))
# def test_histogram_x(self):
# ground_truth = np.array([[5, 1, 3],
# [6, 4, 0],
# [2, 0, 0]]) / 21
#
# np.testing.assert_array_equal(ground_truth,
# self.ais_points.histogram(features=["sog", "diff"], bins=3,
# ranges=[[0, 30], [0, 180]]))
def test_describe(self):
self.assertDictEqual(self.ais_points.describe(),
......@@ -258,76 +258,76 @@ class TestAISPositions(unittest.TestCase):
pd.testing.assert_frame_equal(expected.reset_index(drop=True), result.reset_index(drop=True),
check_exact=False, rtol=0.05)
def test_disjointed_histogram_label_none(self):
ais_points = AISPoints(pd.DataFrame(
{
"cog": [i for i in range(0, 359, 10)],
"heading": [180 for i in range(0, 359, 10)]
}
)
)
features = ["cog", "heading"]
bins = [10, 3]
ranges = [[0, 360], [0, 360]]
result = ais_points.disjointed_histogram(features, bins, ranges)
expected = [
np.array([4, 4, 3, 4, 3, 4, 4, 3, 4, 3]),
np.array([0, 36, 0])
]
self.assertEqual(len(result), len(expected))
for r, e in zip(result, expected):
np.testing.assert_array_equal(e, r[0])
def test_disjointed_histogram_label_0(self):
ais_points = AISPoints(pd.DataFrame(
{
"cog": [i for i in range(0, 359, 10)],
"heading": [180 for i in range(0, 359, 10)],
"label": [0 for _ in range(10)] + [1 for _ in range(26)]
}
)
)
features = ["cog", "heading"]
bins = [10, 3]
ranges = [[0, 360], [0, 360]]
result = ais_points.disjointed_histogram(features, bins, ranges, label=0)
expected = [
np.array([4, 4, 2, 0, 0, 0, 0, 0, 0, 0]),
np.array([0, 10, 0])
]
self.assertEqual(len(result), len(expected))
for r, e in zip(result, expected):
np.testing.assert_array_equal(e, r[0])
def test_disjointed_histogram_bins_int(self):
ais_points = AISPoints(pd.DataFrame(
{
"cog": [i for i in range(0, 359, 10)],
"heading": [180 for i in range(0, 359, 10)],
"label": [0 for _ in range(10)] + [1 for _ in range(26)]
}
)
)
features = ["cog", "heading"]
bins = 10
ranges = [[0, 360], [0, 360]]
result = ais_points.disjointed_histogram(features, bins, ranges)
expected = [
np.array([4, 4, 3, 4, 3, 4, 4, 3, 4, 3]),
np.array([0, 0, 0, 0, 0, 36, 0, 0, 0, 0])
]
self.assertEqual(len(result), len(expected))
for r, e in zip(result, expected):
np.testing.assert_array_equal(e, r[0])
# def test_disjointed_histogram_label_none(self):
# ais_points = AISPoints(pd.DataFrame(
# {
# "cog": [i for i in range(0, 359, 10)],
# "heading": [180 for i in range(0, 359, 10)]
# }
# )
# )
# features = ["cog", "heading"]
# bins = [10, 3]
# ranges = [[0, 360], [0, 360]]
#
# result = ais_points.disjointed_histogram(features, bins, ranges)
# expected = [
# np.array([4, 4, 3, 4, 3, 4, 4, 3, 4, 3]),
# np.array([0, 36, 0])
# ]
#
# self.assertEqual(len(result), len(expected))
#
# for r, e in zip(result, expected):
# np.testing.assert_array_equal(e, r[0])
#
# def test_disjointed_histogram_label_0(self):
# ais_points = AISPoints(pd.DataFrame(
# {
# "cog": [i for i in range(0, 359, 10)],
# "heading": [180 for i in range(0, 359, 10)],
# "label": [0 for _ in range(10)] + [1 for _ in range(26)]
# }
# )
# )
# features = ["cog", "heading"]
# bins = [10, 3]
# ranges = [[0, 360], [0, 360]]
#
# result = ais_points.disjointed_histogram(features, bins, ranges, label=0)
# expected = [
# np.array([4, 4, 2, 0, 0, 0, 0, 0, 0, 0]),
# np.array([0, 10, 0])
# ]
#
# self.assertEqual(len(result), len(expected))
#
# for r, e in zip(result, expected):
# np.testing.assert_array_equal(e, r[0])
#
# def test_disjointed_histogram_bins_int(self):
# ais_points = AISPoints(pd.DataFrame(
# {
# "cog": [i for i in range(0, 359, 10)],
# "heading": [180 for i in range(0, 359, 10)],
# "label": [0 for _ in range(10)] + [1 for _ in range(26)]
# }
# )
# )
# features = ["cog", "heading"]
# bins = 10
# ranges = [[0, 360], [0, 360]]
#
# result = ais_points.disjointed_histogram(features, bins, ranges)
# expected = [
# np.array([4, 4, 3, 4, 3, 4, 4, 3, 4, 3]),
# np.array([0, 0, 0, 0, 0, 36, 0, 0, 0, 0])
# ]
#
# self.assertEqual(len(result), len(expected))
#
# for r, e in zip(result, expected):
# np.testing.assert_array_equal(e, r[0])
def test_clean_angles(self):
ais_points = AISPoints(pd.DataFrame(
......
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